Application of statistical learning and mechanistic modelling towards mapping the substrate electronic space in a Cu-catalyzed Suzuki–Miyaura coupling

Abstract

DFT and statistical learning allow mapping the electronic substrate effects on a Cu-catalyzed Suzuki–Miyaura reaction between iodobenzenes and aryl boronate esters. The resulting substrate map can be used to predict the outcome of similar reactions.